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#!/usr/bin/env python3
"""
Local wrapper for cloud training script
"""
import os
import sys
import argparse
from pathlib import Path
def main():
parser = argparse.ArgumentParser(description='Run cloud training locally')
parser.add_argument('--model_name', type=str, default='local-morphological-transformer', help='Model name')
parser.add_argument('--dataset', type=str, default='10L_90NL', choices=['10L_90NL', '50L_50NL', '90L_10NL'], help='Dataset name')
parser.add_argument('--run', type=str, default='1', choices=['1', '2', '3'], help='Run number')
parser.add_argument('--output_dir', type=str, default='./cloud_output', help='Output directory')
parser.add_argument('--model_dir', type=str, default='./cloud_models', help='Model directory')
parser.add_argument('--wandb_project', type=str, default='morphological-transformer-local', help='WandB project name')
parser.add_argument('--hf_token', type=str, help='Hugging Face token (optional)')
args = parser.parse_args()
# Set environment variables
os.environ['MODEL_NAME'] = args.model_name
os.environ['DATASET_NAME'] = args.dataset
os.environ['RUN_NUMBER'] = args.run
os.environ['DATA_DIR'] = f'./{args.dataset}'
os.environ['OUTPUT_DIR'] = args.output_dir
os.environ['MODEL_DIR'] = args.model_dir
os.environ['WANDB_PROJECT'] = args.wandb_project
if args.hf_token:
os.environ['HF_TOKEN'] = args.hf_token
print(f"🚀 Starting cloud training with:")
print(f" - Model: {args.model_name}")
print(f" - Dataset: {args.dataset}")
print(f" - Run: {args.run}")
print(f" - Output: {args.output_dir}")
print(f" - Models: {args.model_dir}")
print(f" - WandB: {args.wandb_project}")
# Import and run the cloud training script
try:
from scripts.hf_cloud_training import main as cloud_main
cloud_main()
except ImportError as e:
print(f"❌ Failed to import cloud training script: {e}")
sys.exit(1)
except Exception as e:
print(f"❌ Training failed: {e}")
sys.exit(1)
if __name__ == '__main__':
main()
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